where \([]\)  is the channel-wise concatenation operator, and \(c_n\)  is a one channel binary volume for domain labeling, i.e. \(c_1=1, c_2=0, c_3=0\)  for tracer A. \(M\)  is randomly generated over the training process. In parallel, we deploy a discriminator \(D\)  with auxiliary classifier design [1]} for discrimination of source domain (i.e. real/fake) and class domain (i.e. tracer A/B/C).
